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Post‐release monitoring is critical for assessing translocation outcomes. Yet the quality of information gained from monitoring can vary greatly, and perceived monitoring costs often results in reduced monitoring effort. Selecting cost‐effective monitoring strategies that provide high quality data are therefore important for assessing translocation outcomes and making informed management decisions.To compare how monitoring strategy affects information gained, we monitored a toutouwai/North Island robin (Petroica longipes) reintroduction in Aotearoa New Zealand, based on monitoring objectives of determining survival, site fidelity and whether the extent of management was large enough to protect dispersing individuals. We compared how these objectives were met through four monitoring strategies: (1) comprehensive surveys with ground radio telemetry and playback; (2) aerial drone telemetry; (3) dedicated playback by trained surveyors and (4) opportunistic playback by predator control contractors. We undertook a viewshed analysis to determine search coverage of each strategy and compared detection rates, efficiency and cost.Comprehensive ground telemetry and playback, while costly, covered the largest area and provided the most accurate data on dispersal, survival and the translocation outcome. In comparison, opportunistic playback monitoring detected substantially fewer individuals, giving a false impression of low site fidelity and survival and a failed translocation. Although drone telemetry had considerable site‐specific limitations, which limited its effectiveness during our study, it was the most cost‐effective with a high detection rate and low search effort.Synthesis and applications: Our study shows the value of intensive monitoring in facilitating management decisions for wildlife translocations. Comprehensive telemetry and playback, while costly, were invaluable for gaining high quality information on the translocation outcome. Without suitable monitoring, reintroduction outcomes can be difficult to assess and potentially result in unnecessary, ineffective or overly expensive management actions. We recommend that monitoring intensity and methodology should reflect the site, species and level of uncertainty regarding the translocation outcome. Prioritising monitoring can help reduce long‐term costs, increase quality of information gained and allow for more informed management decisions that can improve subsequent translocation outcomes. [ABSTRACT FROM AUTHOR]

Ultrasound B-scan images are traditionally formed from the envelope of the received radiofrequency echoes, but the image texture is dominated by granular speckle patterns. Longstanding efforts at speckle reduction and deconvolution have been developed to lessen the detrimental aspects of speckle. However, we now propose an alternative approach to estimation (and image rendering) of the underlying fine grain scattering density of tissues based on power law constraints. The key steps are a whitening of the spectrum of the received signal while conforming to the original envelope shape and statistics, followed by a power law filtering in accordance with the known scattering behavior of tissues. This multiple step approach results in a high-spatial-resolution map of scattering density that is constrained by the most important properties of scattering from tissues. Examples from in vivo liver scans are shown to illustrate the change in image properties from this framework. [ABSTRACT FROM AUTHOR]

Studying the behavior of electroactive cells, such as firing dynamics and chemical secretion, is crucial for developing human disease models and therapeutics. Following the recent advances in cell culture technology, traditional monolayers are optimized to resemble more 3D, organ‐like structures. The biological and electrochemical complexity of these structures requires devices with adaptive shapes and novel features, such as precise electrophysiological mapping and stimulation in the case of brain‐ and heart‐derived tissues. However, conventional organ‐on‐chip platforms often fall short, as they do not recreate the native environment of the cells and lack the functional interfaces necessary for long‐term monitoring. Origami‐on‐a‐chip platforms offer a solution for this problem, as they can flexibly adapt to the structure of the desired biological sample and can be integrated with functional components enabled by chosen materials. In this review, the evolution of origami‐on‐a‐chip biointerfaces is discussed, emphasizing folding stimuli, materials, and critical findings. In the prospects, microfluidic integration, functional tissue engineering scaffolds, and multi‐organoid networks are included, allowing patient‐specific diagnoses and therapies through computational and in vitro disease modeling. [ABSTRACT FROM AUTHOR]

The utilization of a reverberant shear-wave field in shear-wave elastography has emerged as a promising technique for achieving robust shear-wave speed (SWS) estimation. However, many types of estimators cannot accurately measure SWS within such a complicated 3D wave field. This study introduces an advanced autocorrelation estimator based on angular integration known as the angular integral autocorrelation (AIA) approach to address this issue. The AIA approach incorporates all the autocorrelation data from various angles during measurements, resulting in enhanced robustness to both noise and imperfect distributions in SWS estimation. The effectiveness of the AIA estimator for SWS estimation is first validated using a k-Wave simulation of a stiff branching tube in a uniform background. Furthermore, the AIA estimator is applied to ultrasound elastography experiments, magnetic resonance imaging (MRI) experiments, and optical coherence tomography (OCT) studies across a range of different excitation frequencies on tissues and phantoms, including in vivo scans. The results verify the capacity of the AIA approach to enhance the accuracy of SWS estimation and the signal-to-noise ratio (SNR), even within an imperfect reverberant shear-wave field. Compared to simple autocorrelation approaches, the AIA approach can also successfully visualize and define lesions while significantly improving the estimated SWS and SNR in homogeneous background materials and providing improved elastic contrast between structures within the scans. These findings demonstrate the robustness and effectiveness of the AIA approach across a wide range of applications, including ultrasound elastography, magnetic resonance elastography (MRE), and optical coherence elastography (OCE), for accurately identifying the elastic properties of biological tissues in diverse excitation scenarios. [ABSTRACT FROM AUTHOR]

Background: The timing of behavior and habitat use of nocturnal animals can be influenced by the lunar cycle in nature. The prevalence of artificial light at night (ALAN) has been recognized as a source of environmental pollution. The interaction between ALAN and the lunar cycle on bat behavior is important for understanding anthropogenic effects on bats. We utilized a decade (2012–2022) of acoustic monitoring data collected in North Carolina, United States, to investigate the relationship between bat activity, lunar cycle, and light pollution. We examined whether the amount of lunar illumination affected species-specific nightly activity and whether hourly bat activity patterns varied between nights with different moon phases. We further investigated if the relationship between bat activity and the lunar cycle might be altered by light pollution. Results: We found that seven bat species showed activity variation across nights in relation to the amount of moon illumination when ALAN was absent. In general, bats were less active on full moon nights compared to new moon nights. Light pollution interacted with the bat–lunar relationship in five of the seven species, masking the effect of the lunar cycle. We identified delayed bat activity patterns on nights with a full or waxing moon in seven species, and light pollution altered that pattern in four species. Overall, ALAN was associated with decreased bat activity independent of lunar cycle effects. Conclusions: Our study demonstrated that at a broad spatial scale, ALAN negatively affected many North American temperate bat species and altered their lunar chronobiology. As light pollution is spreading to historically dark areas and habitats, ALAN might couple with other threats, such as the white-nose syndrome or climate change, to cause cascading damage in the environment that depends on ecosystem services such as pest control provided by bats. We argue that further research and conservation actions are needed to mitigate the impact of light pollution. [ABSTRACT FROM AUTHOR]

Background: The prevalence of liver diseases, especially steatosis, requires a more convenient and noninvasive tool for liver diagnosis, which can be a surrogate for the gold standard biopsy. Magnetic resonance (MR) measurement offers potential, however ultrasound (US) has better accessibility than MR. Purpose: This study aims to suggest a multiparametric US approach which demonstrates better quantification and imaging performance than MR imaging‐based proton density fat fraction (MRI‐PDFF) for hepatic steatosis assessment. Methods: We investigated early‐stage steatosis to evaluate our approach. An in vivo (within the living) animal study was performed. Fat inclusions were accumulated in the animal livers by feeding a methionine and choline deficient (MCD) diet for 2 weeks. The animals (n = 19) underwent US and MR imaging, and then their livers were excised for histological staining. From the US, MR, and histology images, fat accumulation levels were measured and compared: multiple US parameters; MRI‐PDFF; histology fat percentages. Seven individual US parameters were extracted using B‐mode measurement, Burr distribution estimation, attenuation estimation, H‐scan analysis, and shear wave elastography. Feature selection was performed, and the selected US features were combined, providing quantification of fat accumulation. The combined parameter was used for visualizing the localized probability of fat accumulation level in the liver; This procedure is known as disease‐specific imaging (DSI). Results: The combined US parameter can sensitively assess fat accumulation levels, which is highly correlated with histology fat percentage (R = 0.93, p‐value < 0.05) and outperforms the correlation between MRI‐PDFF and histology (R = 0.89, p‐value < 0.05). Although the seven individual US parameters showed lower correlation with histology compared to MRI‐PDFF, the multiparametric analysis enabled US to outperform MR. Furthermore, this approach allowed DSI to detect and display gradual increases in fat accumulation. From the imaging output, we measured the color‐highlighted area representing fatty tissues, and the fat fraction obtained from DSI and histology showed strong agreement (R = 0.93, p‐value < 0.05). Conclusions: We demonstrated that fat quantification utilizing a combination of multiple US parameters achieved higher performance than MRI‐PDFF; therefore, our multiparametric analysis successfully combined selected features for hepatic steatosis characterization. We anticipate clinical use of our proposed multiparametric US analysis, which could be beneficial in assessing steatosis in humans. [ABSTRACT FROM AUTHOR]

Gas‐phase reactions of mass‐selected ions with neutrals covers a very broad area of fundamental and applied mass spectrometry (MS). Oftentimes, ion‐molecule reactions (IMR) can serve as a viable alternative to collision‐induced dissociation and other ion dissociation techniques when using tandem MS. This review focuses on the literature pertaining applications of IMR since 2013. During the past decade considerable efforts have been made in analytical applications of IMR, including advances in one of the major techniques for characterization of unsaturated fatty acids and lipids, ozone‐induced dissociation, and the development of a new technique for sequencing of large ions, hydrogen atom attachment/abstraction dissociation. Many advances have also been made in identifying gas‐phase chemistry specific to a functional group in organic and biological compounds, which are useful in structure elucidation of analytes and differentiation of isomers/isobars. With "soft" ionization techniques like electrospray ionization having become mainstream for quite some time now, the efforts in the area of metal ion catalysis have firmly moved into exploring chemistry of ligated metal complexes in their "natural" oxidation states allowing to model individual steps of mechanisms in homogeneous catalysis, especially in combination with high‐level DFT calculations. Finally, IMR continue to contribute to the body of knowledge in the area of chemistry of interstellar processes. [ABSTRACT FROM AUTHOR]

Segmentation of breast ultrasound images is a crucial and challenging task in computer-aided diagnosis systems. Accurately segmenting masses in benign and malignant cases and identifying regions with no mass is a primary objective in breast ultrasound image segmentation. Deep learning (DL) has emerged as a powerful tool in medical image segmentation, revolutionizing how medical professionals analyze and interpret complex imaging data. The UNet architecture is a highly regarded and widely used DL model in medical image segmentation. Its distinctive architectural design and exceptional performance have made it popular among researchers. With the increase in data and model complexity, optimization and fine-tuning models play a vital and more challenging role than before. This paper presents a comparative study evaluating the effect of image preprocessing and different optimization techniques and the importance of fine-tuning different UNet segmentation models for breast ultrasound images. Optimization and fine-tuning techniques have been applied to enhance the performance of UNet, Sharp UNet, and Attention UNet. Building upon this progress, we designed a novel approach by combining Sharp UNet and Attention UNet, known as Sharp Attention UNet. Our analysis yielded the following quantitative evaluation metrics for the Sharp Attention UNet: the Dice coefficient, specificity, sensitivity, and F1 score values obtained were 0.93, 0.99, 0.94, and 0.94, respectively. In addition, McNemar's statistical test was applied to assess significant differences between the approaches. Across a number of measures, our proposed model outperformed all other models, resulting in improved breast lesion segmentation. [ABSTRACT FROM AUTHOR]

In tissues and organs, the extracellular matrix (ECM) helps maintain inter- and intracellular architectures that sustain the structure–function relationships defining physiological homeostasis. Combining fiber scaffolds and cells to form engineered tissues is a means of replicating these relationships. Engineered tissues' fiber scaffolds are designed to mimic the topology and chemical composition of the ECM network. Here, we asked how cells found in the heart compare in their propensity to align their cytoskeleton and self-organize in response to topological cues in fibrous scaffolds. We studied cardiomyocytes, valvular interstitial cells, and vascular endothelial cells as they adapted their inter- and intracellular architectures to the extracellular space. We used focused rotary jet spinning to manufacture aligned fibrous scaffolds to mimic the length scale and three-dimensional (3D) nature of the native ECM in the muscular, valvular, and vascular tissues of the heart. The representative cardiovascular cell types were seeded onto fiber scaffolds and infiltrated the fibrous network. We measured different cell types' propensity for cytoskeletal alignment in response to fiber scaffolds with differing levels of anisotropy. The results indicated that valvular interstitial cells on moderately anisotropic substrates have a higher propensity for cytoskeletal alignment than cardiomyocytes and vascular endothelial cells. However, all cell types displayed similar levels of alignment on more extreme (isotropic and highly anisotropic) fiber scaffold organizations. These data suggest that in the hierarchy of signals that dictate the spatiotemporal organization of a tissue, geometric cues within the ECM and cellular networks may homogenize behaviors across cell populations and demographics. [ABSTRACT FROM AUTHOR]

Conservation management decisions are challenging due to multiple, competing values (objectives) held by various parties, complex management options (alternatives), potential irreversible consequences, ubiquitous uncertainty and opaque governance structures. These complications are exacerbated when target species are highly mobile, utilise aquatic and terrestrial ecosystems and interact with human interests. Even when decisions are made, these challenges may still inhibit management implementation. Decision analyses offer solutions, but are rarely applied in conservation management, especially for highly mobile species across ecosystems.We applied a formal decision analysis for the conservation management of a highly mobile seabird (Kuaka; Whenua Hou Diving Petrel; Pelecanoides whenuahouensis) across ecosystems. Together with Māori (Indigenous Peoples of Aotearoa New Zealand), government staff and industry representatives, we identified seven fundamental objectives and 11 potential alternatives. We predicted consequences of alternatives across objectives using state‐of‐the‐art statistical models, including integrated population models, and expert elicitations hosted through Shiny apps. We then used various decision‐analytical tools to weigh trade‐offs and identify the preferred alternative.The preferred alternative across objectives consisted of a combination of mitigation of vessel‐based light pollution, plant and competition management and inter‐island translocations. This alternative was predicted to provide the most effective conservation outcomes across values and ecosystems and was rapidly implemented in a stepwise fashion following this decision analysis.Synthesis and application. We illustrate that decision analyses provide inclusive environments for all participants despite diverse backgrounds and views, enable rational navigation of complex decision landscapes and facilitate transparent identification of preferred management options across all fundamental values, including Māori value systems and industry concerns. Additionally, we show that decision analyses can rapidly bridge the spaces between research and implementation. Therefore, we argue that the application of decision analyses has great potential to improve the field of conservation. [ABSTRACT FROM AUTHOR]

In the approaches to elastography, two mathematical operations have been frequently applied to improve the final estimate of shear wave speed and shear modulus of tissues. The vector curl operator can separate out the transverse component of a complicated displacement field, and directional filters can separate distinct orientations of wave propagation. However, there are practical limitations that can prevent the intended improvement in elastography estimates. Some simple configurations of wavefields relevant to elastography are examined against theoretical models within the semi-infinite elastic medium and guided waves in a bounded medium. The Miller–Pursey solutions in simplified form are examined for the semi-infinite medium and the Lamb wave symmetric form is considered for the guided wave structure. In both cases, we examine simple but practical wave combinations that can prevent the curl and directional filter operations from directly providing an improved measure of shear wave speed and shear modulus. Additional factors including signal-to-noise and the support of filters also restrict the applicability of these strategies for improving elastographic measures. Thus, some implementations of shear wave excitations applied to the body and to bounded structures within the body are shown to involve waves that are not easily resolved by the vector curl operator and directional filters. These limitations may be overcome by more advanced strategies or simple improvements in baseline parameters including the size of the region of interest and the number of shear waves propagated within. [ABSTRACT FROM AUTHOR]

Objective: The majority of people in the world lack basic access to breast diagnostic imaging resulting in delay to diagnosis of breast cancer. In this study, we tested a volume sweep imaging (VSI) ultrasound protocol for evaluation of palpable breast lumps that can be performed by operators after minimal training without prior ultrasound experience as a means to increase accessibility to breast ultrasound. Methods: Medical students without prior ultrasound experience were trained for less than 2 hours on the VSI breast ultrasound protocol. Patients presenting with palpable breast lumps for standard of care ultrasound examination were scanned by a trained medical student with the VSI protocol using a Butterfly iQ handheld ultrasound probe. Video clips of the VSI scan imaging were later interpreted by an attending breast imager. Results of VSI scan interpretation were compared to the same‐day standard of care ultrasound examination. Results: Medical students scanned 170 palpable lumps with the VSI protocol. There was 97% sensitivity and 100% specificity for a breast mass on VSI corresponding to 97.6% agreement with standard of care (Cohen's κ = 0.95, P <.0001). There was a detection rate of 100% for all cancer presenting as a sonographic mass. High agreement for mass characteristics between VSI and standard of care was observed, including 87% agreement on Breast Imaging‐Reporting and Data System assessments (Cohen's κ = 0.82, P <.0001). Conclusions: Breast ultrasound VSI for palpable lumps offers a promising means to increase access to diagnostic imaging in underserved areas. This approach could decrease delay to diagnosis for breast cancer, potentially improving morbidity and mortality. [ABSTRACT FROM AUTHOR]

There have been numerous declines and extinctions of native fauna in Aotearoa New Zealand since human settlement. Against this background of loss there have been remarkable advances in conservation management, including the use of conservation translocations to reduce extinction risk and restore depauperate ecosystems. Here we review conservation translocations in Aotearoa New Zealand. Our review assembles knowledge from Aotearoa New Zealand's rich history of faunal translocations and describes six key considerations for successfully establishing translocated populations: (1) What values will be met by a translocation? (2) What is the natural and conservation history of the translocation candidate? (3) Does the release site habitat match that of the proposed source population, and if not, why is the release site considered appropriate and can management ameliorate differences? (4) Will dispersal be a problem? (5) Will genetic management be required and how realistic is it that this management will be implemented? (6) What do future developments mean for the management of translocated populations? We discourage a focus on any single element of translocation planning but rather encourage all people involved in translocations, particularly decision makers, to explicitly recognise that successful translocations typically have multiple, values-based objectives. We also support recommendations that the principles of good translocation decision-making are embedded in government policy. [ABSTRACT FROM AUTHOR]

The free space solution to the wave equation in spherical coordinates is well known as a separable product of functions. Re-examination of these functions, particularly the sums of spherical Bessel and harmonic functions, reveals behaviors which can produce a range of useful beampatterns from radially symmetric sources. These functions can be modified by several key parameters which can be adjusted to produce a wide-ranging family of beampatterns, from the axicon Bessel beam to a variety of unique axial and lateral forms. We demonstrate that several special properties of the simple sum over integer orders of spherical Bessel functions, and then the sum of their product with spherical harmonic functions specifying the free space solution, lead to a family of useful beampatterns and a unique framework for designing them. Examples from a simulation of a pure tone 5 MHz ultrasound configuration demonstrate strong central axis concentration, and the ability to modulate or localize the axial intensity with simple adjustment of the integer orders and other key parameters related to the weights and arguments of the spherical Bessel functions. [ABSTRACT FROM AUTHOR]

The ability to engineer complex multicellular systems has enormous potential to inform our understanding of biological processes and disease and alter the drug development process. Engineering living systems to emulate natural processes or to incorporate new functions relies on a detailed understanding of the biochemical, mechanical, and other cues between cells and between cells and their environment that result in the coordinated action of multicellular systems. On April 3–6, 2022, experts in the field met at the Keystone symposium "Engineering Multicellular Living Systems" to discuss recent advances in understanding how cells cooperate within a multicellular system, as well as recent efforts to engineer systems like organ‐on‐a‐chip models, biological robots, and organoids. Given the similarities and common themes, this meeting was held in conjunction with the symposium "Organoids as Tools for Fundamental Discovery and Translation". [ABSTRACT FROM AUTHOR]

Background: Translocation is a common tool in wildlife management and its implementation has resulted in many conservation successes. During translocations, any associated infectious agents are moved with their wildlife hosts. Accordingly, translocations can present a risk of infectious disease emergence, although they also provide an opportunity to restore natural infectious communities ('infectome') and mitigate the long-term risks of reduced natural resistance. Methods: We used metatranscriptomic sequencing to characterise the cloacal infectome of 41 toutouwai (North Island robin, Petroica longipes) that were translocated to establish a new population within the North Island of New Zealand. We also screened for pathogenic bacteria, fungi and parasites. Results: Although we did not detect any known avian diseases, which is a positive outcome for the translocated toutouwai population, we identified a number of novel viruses of interest, including a novel avian hepatovirus, as well as a divergent calici-like virus and four hepe-like viruses of which the host species is unknown. We also revealed a novel spirochete bacterium and a coccidian eukaryotic parasite. Conclusions: The presumably non-pathogenic viruses and microbial species identified here support the idea that most microorganisms likely do not cause disease in their hosts, and that translocations could serve to help restore and maintain native infectious communities. We advise greater surveillance of infectious communities of both native and non-native wildlife before and after translocations to better understand the impact, positive or negative, that such movements may have on both host and infectome ecology. [ABSTRACT FROM AUTHOR]

Customer learning is regarded as a process that alters either individual cognition or the outcomes of socialisation. Understanding how the learning process works enables a brand firm to identify a customer’s latent needs. Prior studies have primarily focused on effectively positioning brand knowledge in the minds of customers, but that linear learning process does not apply to the interactive and proactive social media setting. Based on the uses and gratifications perspective, this study proposes a customer-learning model and analyses 373 online questionnaires using partial least squares structural equation modelling. The empirical results confirm that learning motivation and collaborative learning are two core components of customer learning that have positive influences on satisfaction, which in turn has a positive influence on customer engagement behaviours (CEBs) and loyalty. In addition, learning motivation is the driver of collaborative learning. Finally, CEBs also have a positive influence on loyalty. This study also concludes that the social network brand community is an informative customer-learning platform that is characterised byinteractivity, collaborative learningandco-creation. Theoretical and managerial implications are also discussed. [ABSTRACT FROM PUBLISHER]

While various studies have focused on the significance of computational thinking (CT) for the future career paths of individuals in science, technology, engineering, and mathematics (STEM), few studies have focused on computational thinking for non-STEM college students. This study explores the relationship between computational thinking and learning satisfaction for non-STEM-major college students. A conceptual model is proposed to examine the structural relationships among computational thinking, self-efficacy, self-exploration, enjoyment and learning satisfaction in an AppInventor-based liberal education course. Collecting data from 190 undergraduate students from Taiwan and analyzing the data by using partial least squares (PLS) methods, the research framework confirms the six proposed hypotheses. These results show that both computational thinking and enjoyment play significant roles in both self-exploration and digital self-efficacy. Moreover, digital self-efficacy and self-exploration also have a significant positive influence on learning satisfaction. These findings have implications for influencing the learning outcomes of non-STEM-major college students, computational thinking course instructors, and computational thinking relevant policies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Applied Ecology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In medical imaging, quantitative measurements have shown promise in identifying diseases by classifying normal versus pathological parameters from tissues. The support vector machine (SVM) has shown promise as a supervised classification algorithm and has been widely used. However, the classification results typically identify a category of abnormal tissues but do not necessarily differentiate progressive stages of a disease. Moreover, the classification result is typically provided independently as a supplement to medical images, which contributes to an overload of information sources in the clinic. Hence, we propose a new imaging method utilizing the SVM to integrate classification results into medical images. This framework is called disease-specific imaging (DSI) that produces a color overlaid highlight on B-mode ultrasound images indicating the type, location, and severity of pathology from different conditions. In this article, the SVM training was performed to construct hyperplanes that can differentiate normal, fibrosis, steatosis, and pancreatic ductal adenocarcinoma (PDAC) metastases in livers based on ultrasound echoes. Also, cluster centroids for specific diseases define unique disease axes, and the inner product between measured features and any disease axis selected by the SVM quantifies the disease progression. The features were measured from 2794 ultrasound frames using the H-scan analysis, attenuation estimation, and B-mode image analysis. The performance of our proposed DSI method was evaluated for a preclinical model of steatosis (${n} =400$ frames). The contribution of each feature was assessed, and the results were compared with ground truth from histology. Moreover, the images generated by our DSI were compared with earlier imaging methods of B-mode, H-scan, and histology. The comparisons demonstrate that DSI images yield higher sensitivity to monitor progressive steatosis than B-mode and H-scan and provide a comparable performance with the histology. For the parameter comparison, DSI and H-scan resulted in similar correlation with histology (${r}_{s} =0.83$) but higher than attenuation (${r}_{s} =0.73$) and B-mode (${r}_{s} =0.47$). Therefore, we conclude that DSI utilizing the SVM applied to steatosis can visually represent the classification results with color highlighting, which can simplify the interpretation of classification compared to the traditional SVM result. We expect that the proposed DSI can be used for any medical imaging modality that can estimate multiple quantitative parameters at high resolution. [ABSTRACT FROM AUTHOR]

Objectives: We study the performance of an artificial intelligence (AI) program designed to assist radiologists in the diagnosis of breast cancer, relative to measures obtained from conventional readings by radiologists. Methods: A total of 10 radiologists read a curated, anonymized group of 299 breast ultrasound images that contained at least one suspicious lesion and for which a final diagnosis was independently determined. Separately, the AI program was initialized by a lead radiologist and the computed results compared against those of the radiologists. Results: The AI program's diagnoses of breast lesions had concordance with the 10 radiologists' readings across a number of BI‐RADS descriptors. The sensitivity, specificity, and accuracy of the AI program's diagnosis of benign versus malignant was above 0.8, in agreement with the highest performing radiologists and commensurate with recent studies. Conclusion: The trained AI program can contribute to accuracy of breast cancer diagnoses with ultrasound. Access the CME test here and search by article title. [ABSTRACT FROM AUTHOR]

1. The art of population modelling is to incorporate factors essential for capturing a population's dynamics while otherwise keeping the model as simple as possible. However, it is unclear how optimal model complexity should be assessed, and whether this optimal complexity has been affected by recent advances in modelling methodology. This issue is particularly relevant to small populations because they are subject to complex dynamics but inferences about those dynamics are often constrained by small sample sizes. 2. We fitted Bayesian hierarchical models to long-term data on vital rates (survival and reproduction) for the toutouwai Petroica longipes population reintroduced to Tiritiri Matangi, a 220-ha New Zealand island, and quantified the performance of those models in terms of their likelihood of replicating the observed population dynamics. These dynamics consisted of overall growth from 33 (±0.3) to 160 (±6) birds from 1992-2018, including recoveries following five harvest events for further reintroductions to other sites. 3. We initially included all factors found to affect vital rates, which included inbreeding, post-release effects (PRE), density-dependence, sex, age and random annual variation, then progressively removed these factors. We also compared performance of models where data analysis and simulations were done simultaneously to those produced with the traditional two-step approach, where vital rates are estimated first then fed into a separate simulation model. Parametric uncertainty and demographic stochasticity were incorporated in all projections. 4. The essential factors for replicating the population's dynamics were density-dependence in juvenile survival and PRE, i.e. initial depression of survival and reproduction in translocated birds. Inclusion of other factors reduced the precision of projections, and therefore the likelihood of matching observed dynamics. However, this reduction was modest when the modelling was done in an integrated framework. In contrast, projections were much less precise when done with a two-step modelling approach, and the cost of additional parameters was much higher under the two-step approach. 5. These results suggest that minimization of complexity may be less important than accounting for covariances in parameter estimates, which is facilitated by integrating data analysis and population projections using Bayesian methods. [ABSTRACT FROM AUTHOR]

"Ahuahu: A Conservation Journey in Aotearoa New Zealand" by David Towns is a book that chronicles the author's 50-year career in conservation and the major developments in New Zealand conservation during that time. The book focuses on island eradications and reintroductions, leading up to the current Predator Free New Zealand program, and highlights the involvement of community groups and Indigenous Māori in conservation efforts. While the book is a mix of memoir, popular science, and introductory text, it provides a wealth of information and references for readers interested in conservation. The book also advocates for a broader social and cultural context in conservation biology and emphasizes the importance of individuals like David Towns who combine fieldwork, theory, and management in their conservation efforts. [Extracted from the article]

Purpose: The ability of ultrasound to assess pathology is increasing with the development of quantitative parameters. Among these are a set of parameters derived from the recent H‐scan analysis of subresolvable scattering. The emergence of these quantitative measures of tissue/ultrasound interactions now enables a study of the unique trajectories of multiparametric features in multidimensional space, representing the progression of specific diseases over time. We develop the mathematical and visual tools that are effective for classifying, quantifying, and visualizing the steady progression of several diseases from independent studies, all within a uniform framework. Methods: After applying the H‐scan analysis of ultrasound echoes, we trained a support vector machine (SVM) to classify the unique trajectories of progressive liver disease from fibrosis, steatosis, and pancreatic ductal adenocarcinoma (PDAC) metastasis. Our approaches include the development of trajectory maps and disease‐specific color imaging stains. Results: The multidimensional SVM image classification reached 100% accuracy across the three different studies. Conclusion: H‐scan trajectories can be useful to track the progression of multiple classes of diseases, improving diagnosis, staging, and assessing the response to therapy. [ABSTRACT FROM AUTHOR]

The article discusses issues on queer rights and the current state of European Court of Human Rights (ECHR) jurisprudence on queer rights as of September 2021 by examining the ruling in the cases Zhdanov and Others v. Russia and Alekseyev and Others v. Russia. Other topics include queer people's right to freedom of association and how to convince Russia to comply with the rulings of ECHR.

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We derive closed-form solutions for reverberant elastography in anisotropic elastic media by adapting the framework used in electromagnetic theory to treat transverse isotropic materials. Different sample-setup geometries are analyzed, highlighting their relevance for both optical coherence elastography (OCE) and ultrasound elastography (USE). Numerical simulations using finite elements are used to validate the proposed solutions in practical cases. OCE experiments are conducted in ex vivo chicken muscle samples for the characterization of in-plane and out-of-plane shear modulus assuming a transverse isotropic elastic model. Additionally, we obtained a generalized geometry-independent solution for the isotropic media case, thus unifying previous results for reverberant elastography. [ABSTRACT FROM AUTHOR]

Copyright of Conservation Biology is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A key goal of ecological research is to obtain reliable estimates of population demographic rates, abundance and trends. However, a common challenge when studying wildlife populations is imperfect detection or breeding observation, which results in unknown survival status and reproductive output for some individuals. It is important to account for undetected individuals in population models because they contribute to population abundance and dynamics, and can have implications for population management. Promisingly, recent methodological advances provide us with the tools to integrate data from multiple independent sources to gain insights into the unobserved component of populations. We use data from five reintroduced populations of a threatened New Zealand bird, the hihi (Notiomystis cincta), to develop an integrated population modelling framework that allows missing values for survival status, sex and reproductive output to be modelled. Our approach combines parallel matrices of encounter and reproduction histories from marked individuals, as well as counts of unmarked recruits detected at the start of each breeding season. Integrating these multiple data types enabled us to simultaneously model survival and reproduction of detected individuals, undetected individuals and unknown (never detected) individuals to derive parameter estimates and projections based on all available data, thereby improving our understanding of population dynamics and enabling full propagation of uncertainty. The methods presented will be especially useful for management programmes for populations that are intensively monitored but where individuals are still imperfectly detected, as will be the case for most threatened wild populations. [ABSTRACT FROM AUTHOR]

Diabetes is a disease of insulin insufficiency, requiring many to rely on exogenous insulin with constant monitoring to avoid a fatal outcome. Islet transplantation is a recent therapy that can provide insulin independence, but the procedure is still limited by both the availability of human islets and reliable tests to assess their function. While stem cell technologies are poised to fill the shortage of transplantable cells, better methods are still needed for predicting transplantation outcome. To ensure islet quality, we propose that the next generation of islet potency tests should be biomimetic systems that match glucose stimulation dynamics and cell microenvironmental preferences and rapidly assess conditional and continuous insulin secretion with minimal manual handing. Here, we review the current approaches for islet potency testing and outline technologies and methods that can be used to arrive at a more predictive potency test that tracks islet secretory capacity in a relevant context. With the development of potency tests that can report on islet secretion dynamics in a context relevant to their intended function, islet transplantation can expand into a more widely accessible and reliable treatment option for individuals with diabetes. [ABSTRACT FROM AUTHOR]

Liver disease is increasing in prevalence across the globe. We present here a multiparametric ultrasound (mpUS) imaging approach for assessing nonalcoholic fatty liver disease (NALFD). This study was performed using rats (N = 21) that were fed either a control or methionine and choline deficient (MCD) diet. A mpUS imaging approach that includes H-scan ultrasound (US), shear wave elastography, and contrast-enhanced US measurements were then performed at 0 (baseline), 2, and 6 weeks. Thereafter, animals were euthanized and livers excised for histological processing. A support vector machine (SVM) was used to find a decision plane that classifies normal and fatty liver conditions. In vivo mpUS results from control and MCD diet fed animals reveal that all mpUS measures were different at week 6 (P < 0.05). Principal component analysis (PCA) showed that the H-scan US data contributed the highest percentage to the classification among the mpUS measurements. The SVM resulted in 100% accuracy for classification of normal and high fat livers and 92% accuracy for classification of normal, low fat, and high fat livers. Histology findings found considerable steatosis in the MCD diet fed animals. This study suggests that mpUS examinations have the potential to provide a comprehensive estimation of the main components of early stage NAFLD. [ABSTRACT FROM AUTHOR]

Low winter temperatures are a major driver of hibernation and migration in temperate North American bats. Hibernation and migration in turn affect bat mortality via white-nose syndrome and collisions with wind turbines. To describe winter bat acoustic activity across a wide temperature gradient and to understand species-specific responses to low temperatures, we recorded nightly acoustic activity of bats at 15 sites across the state of North Carolina, United States, from December through February 2016 – 2018. Bat acoustic activity was recorded at all sites during both winters. Nightly probability of bat acoustic presence regressed positively on ambient temperature. Nightly probability of presence in Lasionycteris noctivagans (silver-haired bat) and Eptesicus fuscus (big brown bat) regressed negatively on wind speed. The mean probability of presence within the same winter condition was highest for L. noctivagans , followed by E. fuscus , Perimyotis subflavus (tricolored bat), and Lasiurus cinereus (hoary bat). Differences in species' mean body weight and roosting preference explained part of the variation of the species-specific probability of presence. Our results can be used to predict bat acoustic presence for these species across the southeastern United States in winter, and better understand the potential threats to bats such as white-nose syndrome and wind turbine interactions. [ABSTRACT FROM AUTHOR]

Adipose is a distributed organ that performs vital endocrine and energy homeostatic functions. Hypertrophy of white adipocytes is a primary mode of both adaptive and maladaptive weight gain in animals and predicts metabolic syndrome independent of obesity. Due to the failure of conventional culture to recapitulate adipocyte hypertrophy, technology for production of adult-size adipocytes would enable applications such as in vitro testing of weight loss therapeutics. To model adaptive adipocyte hypertrophy in vitro, we designed and built fat-on-a-chip using fiber networks inspired by extracellular matrix in adipose tissue. Fiber networks extended the lifespan of differentiated adipocytes, enabling growth to adult sizes. By micropatterning preadipocytes in a native cytoarchitecture and by adjusting cell-to-cell spacing, rates of hypertrophy were controlled independent of culture time or differentiation efficiency. In vitro hypertrophy followed a nonlinear, nonexponential growth model similar to human development and elicited transcriptomic changes that increased overall similarity with primary tissue. Cells on the chip responded to simulated meals and starvation, which potentiated some adipocyte endocrine and metabolic functions. To test the utility of the platform for therapeutic development, transcriptional network analysis was performed, and retinoic acid receptors were identified as candidate drug targets. Regulation by retinoid signaling was suggested further by pharmacological modulation, where activation accelerated and inhibition slowed hypertrophy. Altogether, this work presents technology for mature adipocyte engineering, addresses the regulation of cell growth, and informs broader applications for synthetic adipose in pharmaceutical development, regenerative medicine, and cellular agriculture. [ABSTRACT FROM AUTHOR]

Using fatty acids as renewable sources of biofuels requires deoxygenation. While a number of promising catalysts have been developed to achieve this, their operating mechanisms are poorly understood. Here, model molecular systems are studied in the gas phase using mass spectrometry experiments and DFT calculations. The coordinated metal complexes [(phen)M(O2CR)]+ (where phen=1,10‐phenanthroline; M=Ni or Pd; R=CnH2n+1, n≥2) are formed via electrospray ionization. Their collision‐induced dissociation (CID) initiates deoxygenation via loss of CO2 and [C,H2,O2]. The CID spectrum of the stearate complexes (R=C17H35) also shows a series of cations [(phen)M(R')]+ (where R' < C17) separated by 14 Da (CH2) corresponding to losses of C2H4‐C16H32 (cracking products). Sequential CID of [(phen)M(R')]+ ultimately leads to [(phen)M(H)]+ and [(phen)M(CH3)]+, both of which react with volatile carboxylic acids, RCO2H, (acetic, propionic, and butyric) to reform the coordinated carboxylate complexes [(phen)M(O2CR)]+. In contrast, cracking products with longer carbon chains, [(phen)M(R)]+ (R>C2), were unreactive towards these carboxylic acids. DFT calculations are consistent with these results and reveal that the approach of the carboxylic acid to the "free" coordination site is blocked by agostic interactions for R > CH3. [ABSTRACT FROM AUTHOR]

Valuable vesicles: Extracellular vesicles, small membrane-bound particles released from cells, have been shown to have cardioprotective effects. Here, Yadid et al. analyzed the proteins contained in vesicles released from endothelial cells under normoxia and hypoxia and investigated cardioprotective effects on cardiac tissues in vitro. Using a human heart-on-chip composed of cardiomyocytes, the authors showed that endothelial cell–derived vesicles supported metabolic function, tissue contraction, and viability during ischemia-reperfusion injury. This study helps to elucidate the mechanism by which vesicles are cardioprotective in human tissue. Extracellular vesicles (EVs) derived from various stem cell sources induce cardioprotective effects during ischemia-reperfusion injury (IRI). These have been attributed mainly to the antiapoptotic, proangiogenic, microRNA (miRNA) cargo within the stem cell–derived EVs. However, the mechanisms of EV-mediated endothelial signaling to cardiomyocytes, as well as their therapeutic potential toward ischemic myocardial injury, are not clear. EV content beyond miRNA that may contribute to cardioprotection has not been fully illuminated. This study characterized the protein cargo of human vascular endothelial EVs (EEVs) to identify lead cardioactive proteins and assessed the effect of EEVs on human laminar cardiac tissues (hlCTs) exposed to IRI. We mapped the protein content of human vascular EEVs and identified proteins that were previously associated with cellular metabolism, redox state, and calcium handling, among other processes. Analysis of the protein landscape of human cardiomyocytes revealed corresponding modifications induced by EEV treatment. To assess their human-specific cardioprotection in vitro, we developed a human heart-on-a-chip IRI assay using human stem cell–derived, engineered cardiac tissues. We found that EEVs alleviated cardiac cell death as well as the loss in contractile capacity during and after simulated IRI in an uptake- and dose-dependent manner. Moreover, we found that EEVs increased the respiratory capacity of normoxic cardiomyocytes. These results suggest that vascular EEVs rescue hlCTs exposed to IRI possibly by supplementing injured myocytes with cargo that supports multiple metabolic and salvage pathways and therefore may serve as a multitargeted therapy for IRI. [ABSTRACT FROM AUTHOR]

The functional state of the neurovascular unit (NVU), composed of the blood–brain barrier and the perivasculature that forms a dynamic interface between the blood and the central nervous system (CNS), plays a central role in the control of brain homeostasis and is strongly affected by CNS drugs. Human primary brain microvascular endothelium, astrocyte, pericyte, and neural cell cultures are often used to study NVU barrier functions as well as drug transport and efficacy; however, the proteomic and metabolomic responses of these different cell types are not well characterized. Culturing each cell type separately, using deep coverage proteomic analysis and characterization of the secreted metabolome, as well as measurements of mitochondrial activity, the responses of these cells under baseline conditions and when exposed to the NVU‐impairing stimulant methamphetamine (Meth) are analyzed. These studies define the previously unknown metabolic and proteomic profiles of human brain pericytes and lead to improved characterization of the phenotype of each of the NVU cell types as well as cell‐specific metabolic and proteomic responses to Meth. [ABSTRACT FROM AUTHOR]

The blood–brain barrier plays a critical role in delivering oxygen and nutrients to the brain while preventing the transport of neurotoxins. Predicting the ability of potential therapeutics and neurotoxicants to modulate brain barrier function remains a challenge due to limited spatial resolution and geometric constraints offered by existing in vitro models. Using soft lithography to control the shape of microvascular tissues, we predicted blood–brain barrier permeability states based on structural changes in human brain endothelial cells. We quantified morphological differences in nuclear, junction, and cytoskeletal proteins that influence, or indicate, barrier permeability. We established a correlation between brain endothelial cell pair structure and permeability by treating cell pairs and tissues with known cytoskeleton-modulating agents, including a Rho activator, a Rho inhibitor, and a cyclic adenosine monophosphate analog. Using this approach, we found that high-permeability cell pairs showed nuclear elongation, loss of junction proteins, and increased actin stress fiber formation, which were indicative of increased contractility. We measured traction forces generated by high- and low-permeability pairs, finding that higher stress at the intercellular junction contributes to barrier leakiness. We further tested the applicability of this platform to predict modulations in brain endothelial permeability by exposing cell pairs to engineered nanomaterials, including gold, silver–silica, and cerium oxide nanoparticles, thereby uncovering new insights into the mechanism of nanoparticle-mediated barrier disruption. Overall, we confirm the utility of this platform to assess the multiscale impact of pharmacological agents or environmental toxicants on blood–brain barrier integrity. [ABSTRACT FROM AUTHOR]